Large Language Models exhibit two distinct social personalities: adaptive egoists who prioritize personal gain over group welfare, and altruistic agents who cooperate when exposed to social norms. When LLMs are placed in a simulated city environment with communication tools like message boards, their behavior shifts dramatically from selfish to altruistic, demonstrating that social context and communication opportunities can fundamentally transform AI behavior patterns.
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🤯How Schelling's model explains segregation!Hinzugefügt:
And the catch was that they had to reason through their decision themselves without hard-coded rules. Now, what they uncovered was that LLMs aren't all the same. They actually split into two distinct social personalities. The first were the adaptive egoists, 01 mini and 3 mini, [music] sorry.
These models default to selfish moves.
They'll take the personal gain even if it hurts the group. But if you give them a simple social norm message board like a neighborhood chat so they can all converse with each other, they shift.
All of a sudden they start posting things like, "Let's keep densities balanced by staying put." And so their altruism jumps ninefold. All right, so [music] let's dive into the paper. Hints of altruism in large language model agent [music] society. Now, this diagram is showing us how they set up this sort of simulated city. On the left side you've got classic psychology and game theory setups, so rock, paper, scissors, [music] prisoner's dilemma, and all the risk choice paradigms where you pick between different gambles. Each one is very clean and simple.
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